IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v333y2004icp478-496.html
   My bibliography  Save this article

Information flow and emergence of the global patterns in connected neural networks

Author

Listed:
  • Shimizu, Toshihiro

Abstract

In a global network, which consists of many connected local networks, the self-organization processes are studied. The coupling between networks is taken into account in addition to the coupling between neurons. As dynamics of neural network two cases are treated: (1) the chaotic Brownian network and (2) Chua–Yang model of CNN. In the first case it is found that various kinds of global patterns appear in the global system, if some patterns, which are selected autonomously by the system itself, are stored in local networks. The global patterns are generated in terms of two patterns stored in local networks as the background and the figure. In the second case it is investigated how the pattern (or information) stored in a local network propagates in the global network and how the stationary pattern of the global network depends on the coupling between local networks. The relation between dynamics of the local network and the emergence of global patterns in the global network is discussed.

Suggested Citation

  • Shimizu, Toshihiro, 2004. "Information flow and emergence of the global patterns in connected neural networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 333(C), pages 478-496.
    • Handle: RePEc:eee:phsmap:v:333:y:2004:i:c:p:478-496
    DOI: 10.1016/j.physa.2003.10.032
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437103009567
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2003.10.032?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:333:y:2004:i:c:p:478-496. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.